Daily Tech Digest - June 03, 2018

How financial institutions can start with artificial intelligence

Technology 1
AI is increasingly becoming the way for leading financial services to provide everything from customer service to investment advice, says PwC’s Mike Quindazzi. Yet, few banking industry CEOs are considering the impact of AI on future skills, despite the impact that AI is already having on trading desks and reshaping customer interactions. “Protecting the base and avoiding risks is clear and present in the minds of banking leaders,” says Quindazzi. “Many challenges persist due to bias, privacy, trust, lack of trained staff, and regulatory concerns. In the near term, ‘augmented intelligence’ solutions, in which machines assist humans, are quickly making their way into operation.” 'AI or die!' seems to be the rallying cry at every banking conference these days, according to Bradley Leimer, of Explorer Advisory and Capital. “But before going down the path of building and implementing solutions leveraging AI and similar tools, financial institutions must ask themselves where they’re falling short in regard to providing their customers true lifetime value around their finances,” Leimer adds.

Maintaining Malaysia’s digital transformation trajectory

Digital transformation - or DX, as IDC calls it - should be placed as the core strategy and organisations should accelerate the DX pace to thrive in the competitive digital ecosystem. IDC Malaysia's FutureScape 2018 predictions primarily focus on the four pillar technology areas; Cloud, Mobility, Social and Big Data and analytics as well as six innovation accelerators; Augmented and Virtual Reality (AR/VR), Cognitive/AI System, Next-Gen Security, Internet of Things (IoT), 3D Printing and Robotics. Some of IDC's expectations are eye-opening: By 2021, at least 20 percent of Malaysia GDP will be digitised - with growth in every industry driven by digitally-enhanced offerings, operations and relationships; by 2020, investors will use platform/ecosystem, data value, and customer engagement metrics as valuation factors for all enterprises. ... By getting the private sector to partner in funding #MYCYBERSALE 2017 with continued support by MDEC, PIKOM was able to reduce government funding for the project by 40 percent while increasing the Gross Merchandise Value (GMV) or sales generated through the online sales by 55 percent. 

Innovative companies think differently about people

Modern businesses are facing new problems that need fresh thinking. Hiring the same people as before isn’t going to cut it. The variety of perspectives in diverse teams deliver better products, services and customer experiences – and obviously that’s good for business. The ABC recently launched Employable Me, a show about a group of jobseekers aiming to prove that having a neurological condition shouldn’t make them unemployable. It goes to the heart of this need to explore new talent pools. The unemployment rate for people on the autism spectrum was above 30 per cent in 2015, more than three times the rate for people with disability and almost six times the general population. Yet people with these disorders are often highly intelligent. Some have great attention to detail or an intense commitment to delivering high-quality work. They tend to be lateral thinkers and have immeasurable value to offer.

What frustrates Data Scientists in Machine Learning projects?

There is an explosion of interest in data science today. One just needs to insert the tag-line ‘Powered-by-AI’, and anything sells. But, thats where the problems begin. Data science sales pitches often promise the moon. Then, clients raise the expectations a notch up and launch their moonshot projects. Ultimately, it’s left to the data scientists to take clients to the moon, or leave them marooned. An earlier article, ‘4 Ways to fail a Data scientist Job interview’ looked at the key blunders candidates commit in the pursuit of data science. Here, we wade into the fantasy world of expectations from data science projects, and find out the top misconceptions held by clients. Here we’ll talk about the 8 most common myths I’ve seen in machine learning projects, and why they annoy data scientists. If you’re getting into data science, or are already mainstream, these are potential grenades that might be hurled at you. Hence, it would be handy knowing how to handle them.

The blockchain explained for non-engineers

Blockchain buzz is inescapable. And while the technology has transformed some companies and minted fresh millionaires in a dazzlingly short period of time, blockchain is as confounding as it is powerful. If you're confused by the hype, you're not alone. The blockchain is a decentralized, vettable, and secure technology that has, in less than a decade, become a powerful driver of digital transformation poised to help create a new employment economy. Evangelists claim blockchain tech will disrupt industrial supply chains, streamline real estate transactions, and even redefine the media industry. "Think of blockchain as the next layer of the internet," said Tom Bollich, CTO of MadHive. "HTTP gave us websites ... now we have blockchain, which is like a new layer of computing." Employment data seems to validate blockchain's current hype cycle. Google search data indicates a cresting wave of interest in the tech, and according to Indeed.com searches for blockchain-related jobs spiked nearly 1000 percent since 2015. Enterprise organizations like Capital One, Deloitte, ESPN, and eBay are hiring blockchain engineers, retraining project managers to facilitate integrations, and even searching for specialized attorneys.

Unusual Breach Report by Humana Shines Light on Fraud Prevention

In a statement provided to Information Security Media Group, a Humana spokeswoman says the company's initial analyses, and its continuous, ongoing monitoring activities, indicate that fewer than 200 members were impacted in the incident. "The abnormal activity was first identified as an anomaly in our interactive voice response reporting tools. It was noted that an abnormally high abandon rate was being observed from a small number of telephone exchanges," she says. "All evidence in this particular incident indicates that the abnormal activity was benign." Report to State Ryan Kriger, Vermont's assistant attorney general, tells ISMG that Humana reported to the state that 11 Vermont residents were affected by the recent incident. He adds that it's not clear if the incident reported by Humana involving callers who might have been trying to confirm the personally identifiable information of other individuals qualifies as a data breach.

Network security has become irrelevant: Zscaler CEO

Most of the thousands of security companies today sell on the fear of uncertainty. There is so much noise that it is very hard to figure out who to choose. I envisioned the digital transformation taking place in the enterprise, and how it would disrupt traditional network and security models. I asked myself simple questions before starting Zscaler. The world was changing, and employees were beginning to go mobile. More and more applications were becoming SaaS-enabled. I saw a lot of cloud based businesses such as Salesforce, and I figured that security could also be done in the cloud. That’s when I decided to create a security platform where companies can comfortably and securely access SaaS applications, without having to worry buying, deploying and managing. The differentiating factor for us is that we are not looked at as a security product. We are an enabler of business because companies want agility in today’s environment. The idea is to enable businesses to do things better and in a secure manner. Our technology solution is designed to provide security across the cloud stack.

Why a Coffee Shop Will Probably Be Your Workspace Within 10 Years

A study by CTrip of 500 volunteers found that individuals who worked from home were 13.5 percent more efficient and 9 percent more engaged than their peers working in the office. They also took shorter breaks and sick days and took less time off, and attrition rates were 50 percent better. Job satisfaction was higher overall, too. Another study by TINYpulse had similar positive results. Subsequently, more and more companies--particularly those in the transportion, computer, information systems and mathematics industries--are giving workers the leeway to work outside the standard cubicle. These companies don't particularly care where workers work, so long as they finish the jobs they're assigned on time with the expected quality level. In fact, they're using flexible work options to attract new hires, particularly millennials. I should point out here that, in the CTrip study, many workers eventually went back to the office when given the opportunity. Workers want flexibility, but they also wanted to get away from being so isolated and to combat the accurate perception that they wouldn't be considered prominently for bonuses and promotion. 

Parallel programming no longer needs to be an insurmountable obstacle

Parallel code gets its speed benefit from using multiple threads instead of the single one that sequential code uses. Deciding how many threads to create can be a tricky question because more threads don't always result in faster code: if you use too many threads the performance of your code might actually go down. There are a couple of rules that will tell you what number of threads to choose. This depends mostly on the kind of operation that you want to perform and the number of available cores. Computation intensive operations should use a number of threads lower than or equal to the number of cores, while IO intensive operations like copying files have no use for the CPU and can therefore use a higher number of threads. The code doesn’t know which case is applicable unless you tell it what to do. Otherwise, it will default to a number of threads equal to the number of cores.

The Hybrid Cloud Habit You Need to Break

Plenty of small companies start off with a data center in the basement. A few years and a couple satellite offices later, the company decides to move some applications onto a private cloud to accommodate the geography of its workforce. A few years after that, it moves other applications to a public cloud service to stay ahead of traffic surges, lower costs, and add agility. At each stage, the network administrator establishes security protocols for the new environment based on the new architecture. But many network administrators never go back and adjust the data center’s security in light of the new private cloud, and the protocols are seldom adjusted when the second cloud is added. There are lots of reasons for this. Budget plays a role. A planned cloud adoption might have a budget for security that only factors in the new environment. Or the administrator might believe that, having checked for hardware and policy compatibility between the new environments, the security policies are aligned, and there’s no need and no time to go back.

Quote for the day:

"Confidence comes not from always being right but from not fearing to be wrong." -- Peter T. McIntyre

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